CVE-2026-45329
Published: 10 June 2026
Summary
CVE-2026-45329 is a high-severity Improper Input Validation (CWE-20) vulnerability in Espressif Esp-Idf. Its CVSS base score is 7.1 (High).
Operationally, ranked at the 2.0th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-35917
Vulnerability details
ESF-IDF is the Espressif Internet of Things (IOT) Development Framework. In versions 5.5.4 and 6.0, several ESP-TEE secure-service wrappers in esp_secure_services.c and esp_secure_services_iram.c validated only some of the caller-supplied pointer arguments, leaving input pointer arguments unchecked. Because the underlying TEE-protected…
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hardware peripherals (e.g., ECC, SHA, SPI) run in RISC-V machine mode (M-mode) with full address-space access, a caller could supply pointers into TEE-exclusive memory as inputs, causing the peripheral to read TEE memory and return results derived from it to the REE. Depending on the wrapper, the result contains raw bytes from TEE memory, a computed function of TEE memory recoverable through repeated calls, or a single bit per call that forms an oracle for incremental disclosure of TEE-resident sensitive data. This issue has been patched in versions 5.5.5 and 6.0.1.
- CWE(s)
Related Threats
No named actor attribution yet. ATT&CK technique mapping in progress for this CVE.
Affected Assets
Mitigating Controls
Likely Mitigating Controls AI
Per-CVE control mapping for this CVE has not run yet; the list below is derived from the weakness types (CWEs) cited in the NVD entry.
Automated marking applies security attributes to system outputs, making it harder for attackers to exploit unmarked sensitive information leading to unauthorized exposure.
Proper attribute retention and permitted-value enforcement limits unauthorized actors from accessing sensitive information lacking correct labels.
Prevents unauthorized exposure of sensitive information by prohibiting untrusted external systems from processing or storing it.
By enforcing authorization matching prior to sharing, the control reduces the risk of exposing sensitive information to unauthorized actors.
Review and removal of nonpublic information from publicly accessible systems directly prevents exposure of sensitive data to unauthorized actors.
Data mining protection mechanisms detect and block unauthorized bulk extraction of sensitive data, directly mitigating exposure to unauthorized actors.
Literacy training teaches users to recognize and avoid actions that result in unauthorized exposure of sensitive information.
Retaining and monitoring training records confirms personnel have completed privacy and security awareness training on handling sensitive data, reducing the chance of unauthorized exposure due to lack of knowledge.